A database of longterm monitoring of lake ice phenology
A database of longterm monitoring of lake ice phenology
Collaborators and Contributors
- Sapna Sharma
- Thi Nguyen,
- Alessandro Filazzola
- M. Arshad Imrit
- Kevin Blagrave
- Damien Bouffard
- Julia Daly
- Harley Feldman
- Natalie Felsine
- Harrie-Jan Hendricks-Franssen
- Nikolay Granin
- Richard Hecock
- Jan Henning L’Abée-Lund
- Ed Hopkins
- Tom Hoverstad
- Neil Howk
- Paulette Janssen
- Johanna Korhonen
- Hilmar J. Malmquist
- Wlodzimierz Marszelewski
- Shin-Ichiro Matsuzaki
- Yuichi Miyabara
- Kiyoshi Miyasaka
- Alexander Mills
- Joe Norton
- Lolita Olson
- Ted Peters
- David C. Richardson
- Dale Robertson
- Lars Rudstam
- Tom Skramstad
- Larry Smisek
- Danielle Wain
- Holly Waterfield
- Gesa Weyhenmeyer
- Brendan Wiltse
- Huaxia Yao
- Andry Zhdanov
- John J. Magnuson
Data available in the database
## Load libraries
library(tidyverse)
library(DT)
## Load data
lakeChar <- read.csv("data//LakeCharacteristics.csv")
icePheno <- read.csv("data//MainDataset.csv")
datatable(lakeChar, caption="Lake Characteristics")datatable(lakeChar, caption="Lake Ice Phenology")Data
The data within this database are separated into three main files and one ancillary file. - MainDataset.csv: has the lake ice phenology for all 69 lakes. - LakeCharacteristics.csv: has the physical characteristics and coordinates of the lakes in the database. - AllLakeNames.csv: has all alternate names of lakes used in the database. - 69_lakes_ts_minimal.csv: has all the lake ice phenology but in wide format where each column corresponds to a freeze date for years where the lake was intermittent.
Scripts
The qaqc.r and separateMain.r files are used for converted to 69_lakes_ts_minimal.csv into “long” format where only one each column represents ice on and ice off dates. The qaqc.r file also performs some basic quality control and assurance of the dataset. There are two files, create_lake_ice_time_series.py and additional_functions.py that consolated lake names, conduct some quality control, and were responsible for the original data aggregation across multiple files.